水电厂气象水文综合预报调度模型的建立与应用

水电厂气象水文综合预报调度模型整合了降雨预报方案、中长期水文预报方案:洪水预报方案、水库优化调度方案等现有模型系统.降雨数值预报接入水库预报调度系统后,延长了来水预报预见期,结合文中研究的优化调度模型,使水电厂能够提前调整发电计划、调度方案,增加了水电厂的发电效益和水库的防洪减灾社会效益.     

电力期货与期权交易对水电商的风险规避作用

针对水电厂受电力市场电价波动与来水量不确定性的影响，设计了简单的水电厂风险管理案例。将期货与期权的交易模式运用于电力市场中，水电商可以利用期货的套期保值功能规避风险，让购电商和投机商分担电价风险；水电商也可以通过购买看涨或看跌期权，保证水电厂合约外的剩余电量在期望价格销售，减少弃水。     

广东粤电水电厂群防汛调度决策系统

为提高水电厂的防洪、抗洪能力，指导水库做好预报、调度、防汛决策等工作，建设了粤电水电厂群防汛调度决策系统。该系统由粤电中心站和所属8个水电厂分中心站组成，是一个集实时数据采集与处理、水务计算与管理、水文资料整编、水库水文预报、水库防洪调度、水库优化调度、防汛业务管理等功能于一体的水电厂群防汛调度决策系统。文中简要介绍该系统的建设过程、网络结构、系统功能及应用情况。     

不同交易方式下的梯级水电厂日优化运行

研究了发电侧电力市场中限量竞价完全竞价下的梯级水电厂日优化运行问题，分别建立了优化计算模型，并给出了统一化处理的数学模型和求解方法。模型中除考虑了系统边际电价、合同电价和合同电量的因素外，还考虑了系统对各电厂的出力要求：算例表明，模型合理，算法有效，计算结果可作为梯级水电厂日前交易市场中电量申报的基础，效益显著。     

紧水滩梯级水电站水调自动化系统介绍

水情水调自动化系统是一项涉及水文、通信、计算机及网络技术的复杂系统工程，主要依靠先进的采集和传输技术，及时准确地获取水电站流域和其他相关系统的水文、气象和水库运行信息，利用数据库管理技术，进行在线水文预报、优化调度和水库调度优化管理等，同时支持水电厂和电网的经济调度，在保证水电站的防洪安全、电网安全经济运行等方面能发挥出显著的经济和社会效益。     

浅析水电厂调峰弃水损失电量的计算方法

水电厂调峰弃水损失电量是衡量水电厂和电网水库调度工作的一个重要指标，本文分析了原国家电力公司颁布的水电厂调峰弃水损失电量计算方法，指出该方法中计算公式有不合理之处，提出了修改后的理论计算公式与实际应用时的水电厂调峰弃水损失电量计算公式。     

基于博弈论的水电厂竞价上网

应用博弈论方法分析水、火电厂各方在市场机制下的行为机理以及影响水电电价的因素，探索水电厂在竞价上网时应采取的对策。根据水电厂的特性，分别考虑水电厂与火电厂的博弈、水电厂之间的博弈以及调峰电厂的博弈问题；通过估计其他发电厂的竞价行为，得到水电厂的竞价上网博弈模型，其结果可用于水电厂的经济运行，为水电厂管理提供指导。     

基于弃水风险率控制的水库预泄调度方法

针对调节能力有限的电站多存在汛期弃水现象,结合中期径流预报,开展水库预泄调度研究。首先建立预报与风险的直接相关模型,量化水库弃水风险,以风险范围作为控制水库预泄幅度的依据,根据逐日径流预报信息,调整面临时刻水库调度决策。以普定水电站为例的实际调度结果表明,基于弃水风险率控制的水库预泄方法能够有效减少蓄水期弃水电量,而且可保证水库汛末水位。     

WZ．530三峡梯级水库水情测报系统建设稳步推进

据中国三峡工程报报道，长江流域水情站网将为梯级联合调度提供强有力的技术保障，促进中国长江三峡工程开发总公司水电事业建设健康、全面、协调和可持续发展，是提升公司核心竞争力的重要基础设施之一，项目建成将提高175m蓄水高程条件下水文预报的预见期，准确做出三峡入库流量预报，减少不合格电量及水库弃水损失，满足梯级水库调度的需要，是一套集水情信息采集、水文预报、水库调度、会商查询、水情信息发布等功能为一体的水库调度作业系统。     

岩滩电厂水库调度自动化系统规划设计

水库调度自动化以水情自动测报为基础，是一个集通信、遥测、水文预报、水库调度、计算机网络及水务管理于一体的自动化系统，对水电厂的安全经济运行具有巨大的促进作用，是“国际一流水电厂”不可缺少的条件。本文系统地介绍了岩滩水库调度自动化系统的规划设计以及功能要求等。     

利用水文预报进行水电站水库汛期预报调度

充分利用水文信息是协调水库防洪与兴利之间矛盾的有效方法；在满足防洪安全的前提下，可以在未发生洪水时期抬高水库运行水位，在洪水入库以前将库水位降至共限制水位，从而提高径流式不电站发电运行效益和调度水平。沙溪口水电站利用水文预报进行水库汛期预报调度效益显著。     

水电侧竞价上网决策支持系统框架设计

在对水电参与电力市场竞争进行系统分析的基础上,提出在电力市场竞争环境下水电侧电力市场报价辅助决策支持系统的框架设计方案。该方案从系统的设计原则、系统平台整体设计及具体功能设计等方面进行了详细的描述和分析,为水电发电商更好地参与电力市场及辅助服务市场提供有力的技术支持和保障。     

Price-maker型水电厂策略性报价

用古诺模型研究了Price-maker型水电厂在电力市场下的策略报价问题.将系统中各厂商的竞争简化为己方和虚拟对手组成的双人博弈,提出一种基于历史数据、分析对手行为的可行方法.该方法通过分析历史可获得数据,求取对手成本函数参数及系统的逆需求函数,由此获得合理的对手策略估计,并求取在此可能对手策略下的己方最优策略,从而达到己方收益最大的目标.     

电力市场规则及水电竞价浅析

从电价机制、市场模式、竞价空间以及开放的市场种类等方面入手,对目前各区域电力市场规则进行简要比较,分析了这些市场规则的不同特点,以及这些规则对水电企业的影响.针对水电参与市场竞价存在的困难,阐述了开放发电权转让以及梯级水电报价单元选取的问题,并对水电企业在这些市场规则下的应对策略做了一些探讨.     

三峡水库实时调度水文气象预报应用风险及控制

为量化水文气象预报误差对水库实时预报调度的影响,以三峡水库为例,基于其历年水文气象预报信息的误差分析成果,假定入库过程,并叠加对应不同概率的预报误差,以此作为水库调洪演算模型的输入。分析了不同预见期、不同保证率水文气象误差条件下,不超过风险控制点的库水位指标,提出了三峡水库实时预报调度风险控制策略,可为水库科学调度提供参考。     

Enhancing Inflow Forecasting Model at Aswan High Dam Utilizing Radial Basis Neural Network and Upstream Monitoring Stations Measurements

The Nile River is considered the main life artery for so many African countries especially Egypt. Therefore, it is of the essence to preserve its water and utilize it very efficiently. Developing inflow-forecasting model is considered the technical way to effectively achieve such preservation. The hydrological system of the Nile River under consideration has several dams and barrages that are equipped with control gates. The improvement of these hydraulic structures’ criteria for operation can be assessed if reliable forecasts of inflows to the reservoir are available. Recently, the authors developed a forecasting model for the natural inflow at Aswan High Dam (AHD) based on Artificial Intelligence (AI). This model was developed based on the historical inflow data of the AHD and successfully provided accurate inflow forecasts with error less than 10%. However, having several forecasting models based on different types of data increase the level of confidences of the water resources planners and AHD operators. In this study, two forecasting model approach based on Radial Basis Function Neural Network (RBFNN) method for the natural inflow at AHD utilizing the stream flow data of the monitoring stations upstream the AHD is developed. Natural inflow data collected over the last 30 years at four monitoring stations upstream AHD were used to develop the model and examine its performance. Inclusive data analysis through examining cross-correlation sequences, water traveling time, and physical characteristics of the stream flow data have been developed to help reach the most suitable RBFNN model architecture. The Forecasting Error (FE) value of the error and the distribution of the error are the two statistical performance indices used to evaluate the model accuracy. In addition, comprehensive comparison analysis is carried out to evaluate the performance of the proposed model over those recently developed for forecasting the inflow at AHD. The results of the current study showed that the proposed model improved the forecasting accuracy by 50% for the low inflow season, while keep the forecasting accuracy in the same range for the high inflow season.     

Benefit and Risk Balance Optimization for Stochastic Hydropower Scheduling

Limited by inflow forecasting methods, the forecasting results are so unreliable that we have to take their uncertainty and risk into account when incorporating stochastic inflow into reservoir operation. Especially in the electricity market, punishment often happens when the hydropower station does not perform as planned. Therefore, focusing on the risk of power generation, a benefit and risk balance optimization model (BRM) which takes stochastic inflow as the major risk factor is proposed for stochastic hydropower scheduling. The mean-variance theory is firstly introduced into the optimal dispatching of hydropower station, and a variational risk coefficient is employed to give service to managers’ subjective preferences. Then, the multi-period stochastic inflow is simulated by multi-layer scenario tree. Moreover, a specific scenario reduction and reconstruction method is put forward to reduce branches and computing time accordingly. Finally, the proposed model is applied to the Three Gorges Reservoir (TGR) in China for constructing a weekly generation scheduling in falling stage. Compared to deterministic dynamic programming (DDP) and stochastic dynamic programming (SDP), BRM achieves more satisfactory performance. Moreover, the tradeoffs for risk-averse decision makers are discussed, and an efficient curve about benefit and risk is formed to help make decision.     

Reservoir Operation Incorporating Hedging Rules and Operational Inflow Forecasts

Reservoir operation incorporating a naïve hedging strategy and operational inflow forecasting is studied in this paper. Gridded precipitation forecasts from climate model, ECHAM4.5, are used as potential predictors for reservoir inflow forecasting. In building a statistical predicting model, principal component analysis (PCA) is used to reduce the dimension of the regression model. Performance evaluation indices, including water supply satisfaction ratio, environmental flow satisfaction ratio, end-of-month storage satisfaction ratio and flood prevention capacity index, are defined. Three scenarios where a naïve hedging operation rule under different set of reservoir inflow are investigated. These are evaluated for a water supply reservoir, Falls Lake Reservoir, at Neuse River in the southeast United State. Reservoir simulation with monthly average inflow serves as a benchmark. The utility of operational inflow forecasts is quantified by the improvements of performance indices. Results show that reservoir operation under perfect inflow forecasting has the highest values for most indices. Compared to climatology, operational inflow forecasts result in higher index values. Among all the performance indices, end-of-month storage satisfaction ratio is the most sensitive index to inflow information. Limitation of this study and further work is also discussed.     

郁江梯级水电站（贵港和桂平水电站）水调自动化系统建设及功能

为满足水电站现代化管理和水库科学调度运行的要求,广西西江航运建设发展有限责任公司建设了郁江梯级水电站（贵港和桂平水电站）水调自动化系统（以下简称水调自动化系统）。通过对流域水情、梯级相关电站的电力生产和水库调度信息进行实时采集,自动送到水调自动化系统进行在线信息管理,实现了以此为依据做出准确的洪水预报、梯级水库群优化调度等功能,提高了郁江流域梯级贵港和桂平水电站的管理水平和水能利用率。同时针对建设与应用过程中遇到的问题进行了分析,为水调自动化系统的完善和发展指明了方向。